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Database Systems Chapter 1

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Title: Database Systems Chapter 1


1
Database SystemsChapter 1
  • ITM 354

2
File Processing Systems
3
Database Approach
4
Database vs. File-based
  • Miniworld as data source
  • Universe of Discourse (UOD)
  • Logically integrated files
  • Intended users and applications
  • Shared and Self-describing

Compared with file-based approach - program-data
independence - multiple view of data - multi-user
transaction processing
5
Types of Databases and Database Applications
  • Numeric and Textual Databases (e.g. IRS CADE)
  • Multimedia Databases (e.g. Cortina)
  • Geographic Information Systems (GIS)
  • Data Warehouses
  • Real-time and Active Databases

6
Basic Definitions
  • Database A collection of related data.
  • Data Known facts that can be recorded and have
    an implicit meaning.
  • Mini-world Some part of the real world about
    which data is stored in a database. For example,
    student grades and transcripts at a university.
  • Database Management System (DBMS) A collection
    of software to facilitate the creation and
    maintenance of a DB.
  • Database System The DBMS software together with
    the data. Sometimes, applications are also
    included.

7
Database System Environment
Users/Programmers
Application Programs/Queries
DBMS Software
Software to Process Queries/Programs
Software to Access Stored Data
Stored DB Definition (Meta-Data)
Stored Database
8
Why the Database Approach?
  • Application needs constantly changing
  • Ad hoc questions need rapid answers
  • Need to reduce long lead times and high cost in
    new application development
  • Lots of data shared throughout the organization
  • Need to improve data consistency and control
    access to data
  • Substantial dedicated programming assistance
    typically not available

9
Core DB Technology Trend
  • Relational Database
  • Distributed Database
  • Multi-dimensional databases
  • Object Relational Database
  • Object-Oriented Database
  • Multimedia Database
  • Intelligent Database
  • Data warehousing, data marts, data mining
  • Web-based Databases

10
DB Time Line
11
DBMS
  • A collection of software
  • manage different applications for a multi-user
    database system
  • enable users to define/create and manipulate data
  • Basic functions
  • multiple user interfaces
  • controlled redundancy
  • integrity control
  • security authorization protection
  • concurrency recovery control

12
Example Database (with Conceptual Data Model)
  • Mini-world for the example Part of a UNIVERSITY
    environment.
  • Some mini-world entities
  • STUDENTs
  • COURSEs
  • SECTIONs (of COURSEs)
  • (academic) DEPARTMENTs
  • INSTRUCTORs
  • Note The above could be expressed in the
    ENTITY-RELATIONSHIP data model.

13
Example Database (with Conceptual Data Model) 2.
  • Some mini-world relationships
  • SECTIONs are of specific COURSEs
  • STUDENTs take SECTIONs
  • COURSEs have prerequisite COURSEs
  • INSTRUCTORs teach SECTIONs
  • COURSEs are offered by DEPARTMENTs
  • STUDENTs major in DEPARTMENTs
  • Note The above could be expressed in the
    ENTITY-RELATIONSHIP data model.

14
(No Transcript)
15
Example E-R Model
16
Relational Logical Schema Example
17
Example Relational Database Snapshot
18
Features of the E-R Model
  • Relationships are just as important as
    entitiesthey are data that need to be stored in
    the DB
  • Most relationships are binary, but they may be
    ternary (or more!) as well
  • Questions
  • What is the relationship between three binary
    relationships and a ternary relationship?
  • Why are there two relationships between projects
    and employees?

19
Main Characteristics of the Database Approach
  • Self-describing nature of a database system A
    DBMS catalog stores the description of the
    database. The description is called meta-data).
    This allows the DBMS software to work with
    different databases.
  • Insulation between programs and data Called
    program-data independence. Allows changing data
    storage structures and operations without having
    to change the DBMS access programs.

20
Main Characteristics of the Database Approach 2
  • Data Abstraction A data model is used to hide
    storage details and present the users with a
    conceptual view of the database.
  • Support of multiple views of the data Each user
    may see a different view of the database, which
    describes only the data of interest to that
    user.

21
Main Characteristics of the Database Approach 3.
  • Sharing of data and multi-user transaction
    processing allowing a set of concurrent users to
    retrieve and to update the database.
  • Concurrency control within the DBMS guarantees
    that each transaction is correctly executed or
    completely aborted.
  • OLTP (Online Transaction Processing) is a major
    part of database applications.

22
Database Users
  • Users may be divided into
  • those who actually use and control the content
    (called Actors on the Scene)
  • those who enable the database to be developed and
    the DBMS software to be designed and implemented
    (called Workers Behind the Scene).

23
Database Users 2.
  • Actors
  • Database administrators responsible for access
    to the database, for coordinating and monitoring
    its use, acquiring software/hardware resources,
    controlling its use and monitoring run-time
    performance.
  • Database Designers responsible to define the
    content, structure, constraints, and functions or
    transactions against the database. They
    communicate with the end-users and understand
    their needs.
  • End-users use the data for queries, reports and
    some even update database content.

24
Other DBS Personnel
  • System analysts and application programmers
  • Operators and maintenance personnel
  • Tool developers
  • DBMS Designers and Programmers

25
Advantages of Using the Database Approach
  • More information from given data
  • Ad hoc queries can be performed
  • Redundancy can be reduced
  • Inconsistency can be avoided
  • Security restriction can be applied
  • Data independence
  • more cost-effective reduced development time,
    flexibility, economies of scale

26
Advantages of Using the Database Approach - 2
  • Controlling redundancy in data storage and in
    development and maintenance.
  • Sharing of data among multiple users.
  • Providing persistent storage for program objects
    (in Object-oriented DBMSs see Chs. 20-22)
  • Providing storage structures for efficient query
    processing

27
Advantages of Using the Database Approach 3.
  • Providing backup and recovery services.
  • Providing multiple interfaces to different
    classes of users.
  • Representing complex relationships among data.
  • Enforcing integrity constraints on the database.
  • Drawing Inferences and Actions using rules

28
Disadvantages of Using the Database Approach
  • Expensive
  • hardware, software, personnel, processing
    overhead, operating cost , etc.
  • DBMS generality overhead
  • gt performance issue
  • Increased vulnerability to failure
  • Recovery is more complex

When should you not use a DBMS????
29
Additional Implications of the Database Approach
  • Potential for enforcing standards
  • crucial for the success of database applications
    in large organizations
  • standards refer to data item names, display
    formats, screens, report structures, meta-data
    (description of data) etc.
  • Reduced application development time
  • incremental time to add each new application is
    reduced.

30
Additional Implications of the Database Approach
2.
  • Flexibility to change data structures database
    structure may evolve as new requirements are
    defined.
  • Availability of up-to-date information very
    important for on-line transaction systems such as
    airline, hotel, car reservations.
  • Economies of scale by consolidating data and
    applications across departments wasteful overlap
    of resources and personnel can be avoided.

31
Historical Development of Database Technology
  • Early Database Applications Hierarchical and
    Network Models were introduced in mid 1960s and
    dominated the 70s. A bulk of the worldwide
    database processing still uses these models.
  • Relational Model based systems originally
    introduced in 1970 this model was heavily
    researched and experimented with in IBM and
    universities. Relational DBMS products emerged in
    the 1980s.

32
Historical Development of Database Technology 2.
  • Object-oriented applications OODBMSs were
    introduced in late 1980s and early 1990s to cater
    to the need of complex data processing in CAD and
    other applications. Their use is not large.
  • Data on the Web and E-commerce Applications Web
    contains data in HTML with links among pages.
    E-commerce is using standards like XML (eXtended
    Markup Language).

33
Extending Database Capabilities
  • New functionality is being added to DBMSs in the
    following areas
  • Scientific Applications
  • Image Storage and Management
  • Audio and Video data management
  • Data Mining
  • Spatial data management
  • Time Series and Historical Data Management
  • The above gives rise to new research and
    development in incorporating new data types,
    complex data structures, new operations and
    indexing schemes in database systems.

34
When NOT to use a DBMS
  • Main inhibitors (costs) of using a DBMS
  • High initial investment and possible need for
    additional hardware.
  • Overhead for providing generality, security,
    concurrency control, recovery, and integrity
    functions.
  • When a DBMS may be unnecessary
  • If the database and applications are simple, well
    defined, and not expected to change.
  • If there are stringent real-time requirements
    that may not be met because of DBMS overhead.
  • If access to data by multiple users is not
    required.

35
When NOT to use a DBMS 2.
  • When no DBMS may suffice
  • If the database system is not able to handle the
    complexity of data because of modeling
    limitations
  • If the database users need special operations not
    supported by the DBMS.

36
System Overview
OLCP On-Line Complex Processing data mining
knowledge discovery
OLAP On-Line Analytical Processing Data
Warehousing Data Marts
EIS
DSS
DP
OLTP On-line Transaction Processing Operational
databases Legacy systems
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